EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments
2023-04-14Code Available1· sign in to hype
Federico Bianchi, Patrick John Chia, Ciro Greco, Claudio Pomo, Gabriel Moreira, Davide Eynard, Fahd Husain, Jacopo Tagliabue
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/reclist/evalrs-kdd-2023OfficialIn papernone★ 30
Abstract
EvalRS aims to bring together practitioners from industry and academia to foster a debate on rounded evaluation of recommender systems, with a focus on real-world impact across a multitude of deployment scenarios. Recommender systems are often evaluated only through accuracy metrics, which fall short of fully characterizing their generalization capabilities and miss important aspects, such as fairness, bias, usefulness, informativeness. This workshop builds on the success of last year's workshop at CIKM, but with a broader scope and an interactive format.